54 research outputs found
Towards robust and effective shape prior modeling: sparse shape composition
No full textOrgan shape plays an important role in many clinical practices, including diagnosis, surgical planning and treatment evaluation. It is usually derived from medical images using low level appearance cues. However, due to diseases and imaging artifacts, low level appearance cues are often weak or misleading. In this situation, shape priors become critical to infer and refine the shape derived from image appearances. Effective modeling of shape priors is challenging because: 1) shape variations are complex and cannot always be modeled by parametric probability distributions; 2) a shape instance derived from image appearance cues (called an input shape) may have significant errors; and 3) local details of an input shape may be important for clinical purposes but difficult to preserve if they are not statistically significant in the training data. In this paper we propose a novel Sparse Shape Composition model (SSC) to address these three challenges in a unified framework. With our method, a sparse set of shapes is selected from the shape repository and composed together to infer and refine an input shape. This way, the prior information is implicitly incorporated on-the-fly. Our model leverages two sparsity observations of the input shape instance: 1) the input shape can be approximately represented by a sparse linear combination of shapes in the shape repository; 2) parts of the input shape may contain large errors but such errors are sparse. Our model is formulated as a sparse learning problem. Using norm relaxation, it can be solved by an efficient expectation-maximization (EM) framework. Furthermore, this model is extended to effectively handle multi-resolution, local shape priors and hierarchical priors. We also propose a framework to generate high quality training data in 3D. Our framework includes geometry processing methods and shape registration algorithms. The proposed shape prior model is extensively validated on five different medical applications: 2D lung localization in chest X-ray images, 3D liver segmentation in low-dose Computed Tomography (CT) scans, 3D segmentation of multiple rodent brain structures in Magnetic Resonance (MR) microscope, real time tracking of left ventricles in Magnetic Resonance Imaging (MRI), and high resolution CT reconstruction. Compared to state-of-the-art methods, our model exhibits better performance in all these studies.Ph. D.Includes bibliographical referencesIncludes vitaby Shaoting Zhan
Interannual and seasonal variability of glacier surface velocity in the parlung zangbo basin, tibetan plateau
No full textMonitoring glacier flow is vital to understand the response of mountain glaciers to environmental forcing in the context of global climate change. Seasonal and interannual variability of surface velocity in the temperate glaciers of the Parlung Zangbo Basin (PZB) has attracted significant attention. Detailed patterns in glacier surface velocity and its seasonal variability in the PZB are still uncertain, however. We utilized Landsat-8 (L8) OLI data to investigate in detail the variability of glacier velocity in the PZB by applying the normalized image cross-correlation method. On the basis of satellite images acquired from 2013 to 2020, we present a map of time-averaged glacier surface velocity and examined four typical glaciers (Yanong, Parlung No.4, Xueyougu, and Azha) in the PZB. Next, we explored the driving factors of surface velocity and of its variability. The results show that the glacier centerline velocity increased slightly in 2017–2020. The analysis of meteorological data at two weather stations on the outskirts of the glacier area provided some indications of increased precipitation during winter-spring. Such increase likely had an impact on ice mass accumulation in the up-stream portion of the glacier. The accumulated ice mass could have caused seasonal velocity changes in response to mass imbalance during 2017–2020. Besides, there was a clear winter-spring speedup of 40% in the upper glacier region, while a summer speedup occurred at the glacier tongue. The seasonal and interannual velocity variability was captured by the transverse velocity profiles in the four selected glaciers. The observed spatial pattern and seasonal variability in glacier surface velocity suggests that the winter-spring snow might be a driver of glacier flow in the central and upper portions of glaciers. Furthermore, the variations in glacier surface velocity are likely related to topographic setting and basal slip caused by the percolation of rainfall. The findings on glacier velocity suggest that the transfer of winter-spring accumulated ice triggered by mass conservation seems to be the main driver of changes in glacier velocity. The reasons that influence the seasonal surface velocity change need further investigation.Optical and Laser Remote Sensin
Changes in glacier albedo and the driving factors in the Western Nyainqentanglha Mountains from 2001 to 2020
No full textGlacier surface albedo dominates glacier energy balance, thus strongly affecting the glacier mass balance. Glaciers in the Western Nyainqentanglha Mountains (WNM) experienced large mass losses in the past two decades, but long-term changes of glacier albedo and its drivers are less understood. In this study, we retrieved glacier albedo with MODIS reflectance data to characterize the spatiotemporal variability of albedo from 2001 to 2020. Air temperature, rainfall, snowfall and deposition of light-absorbing impurities (LAIs) were evaluated as potential drivers of the observed variability in glacier albedo. The results showed that: (1) the glacier albedo experienced large inter-annual fluctuations, with the mean albedo being 0.552 ± 0.002 and a clear decreasing trend of 0.0443 ± 2 × 10-4 dec-1 in the WNM. The fastest decline was observed in autumn and in the vicinity of the equilibrium line altitude, indicating an extended melt season and an expansion of the ablation region to higher elevation; (2) local meteorology and LAIs deposition are the main drivers of glacier albedo change, but their effects on seasonal albedos are different due to different glacier processes. Both air temperature and the balance between liquid and solid precipitation affect summer and autumn albedos due to glacier ablation. Air temperature is the main driver of spring and winter albedos due to sublimation and metamorphism of snow, while snowfall carried by westerlies has limited influence on these two seasonal albedos due to less snowfall. LAIs mainly affect spring albedo due to high concentration coupled with the southerly wind in spring. These findings highlight the significance of changes in glacier albedo and the key role of local meteorology and LAIs deposition in determining such changes, which play an important role in glaciological and cryosphere processes. Optical and Laser Remote Sensin
Glacier area and snow cover changes in the range system surrounding tarim from 2000 to 2020 using google earth engine
No full textGlacier and snow are sensitive indicators of regional climate variability. In the early 21st century, glaciers in the West Kunlun and Pamir regions showed stable or even slightly positive mass budgets, and this is anomalous in a worldwide context of glacier recession. We studied the evolution of snow cover to understand whether it could explain the evolution of glacier area. In this study, we used the thresholding of the NDSI (Normalized Difference Snow Index) retrieved with MODIS data to extract annual glacier area and snow cover. We evaluated how the glacier trends related to snow cover area in five subregions in the Tarim Basin. The uncertainty in our retrievals was assessed by comparing MODIS results with the Landsat-5 TM in 2000 and Landsat-8 OLI in 2020 glacier delineation in five subregions. The glacier area in the Tarim Basin decreased by 1.32%/a during 2000–2020. The fastest reductions were in the East Tien Shan region, while the slowest relative reduction rate was observed in the West Tien Shan and Pamir, i.e., 0.69%/a and 1.08%/a, respectively, during 2000–2020. The relative glacier stability in Pamir may be related to the westerlies weather system, which dominates climate in this region. We studied the temporal variability of snow cover on different temporal scales. The analysis of the monthly snow cover showed that permanent snow can be reliably delineated in the months from July to September. During the summer months, the sequence of multiple snowfall and snowmelt events leads to intermittent snow cover, which was the key feature applied to discriminate snow and glacier.Optical and Laser Remote Sensin
The impact of demographic dynamics on food consumption and its environmental outcomes: Evidence from China
No full textWith increasing population and changing demographics, food consumption has experienced a significant transition in quantity and quality. However, a dearth of knowledge remains regarding its environmental impacts and how it responds to demographic dynamics, particularly in emerging economies like China. Using the two-stage Quadratic Almost Demand System (QUAIDS) model, this study empirically examines the impact of demographic dynamics on food consumption and its environmental outcomes based on the provincial data from 2000 to 2020 in China. Under various scenarios, according to changes in demographics, we extend our analysis to project the long-term trend of food consumption and its environmental impacts, including greenhouse gas (GHG) emissions, water footprint (WF), and land appropriation (LA). The results reveal that an increase in the proportion of senior people significantly decreases the consumption of grain and livestock meat and increases the consumption of poultry, egg, and aquatic products, particularly for urban residents. Moreover, an increase in the proportion of males in the population leads to higher consumption of poultry and aquatic products. Correspondingly, in the current scenario of an increased aging population and sex ratio, it is anticipated that GHG emissions, WF, and LA are likely to decrease by 1.37, 2.52, and 3.56%, respectively. More importantly, in the scenario adhering to the standards of nutritional intake according to the Dietary Guidelines for Chinese Residents in 2022, GHG emissions, WF, and LA in urban areas would increase by 12.78, 20.94, and 18.32%, respectively. Our findings suggest that changing demographics should be considered when designing policies to mitigate the diet-environment-health trilemma and achieve sustainable food consumption
Does internet use benefit the mental health of older adults? Empirical evidence from the China health and retirement longitudinal study
No full textThe mental health (MH) of older adults is a prominent public health concern. However, research regarding the impact of emerging Internet use on MH among older adults remains limited, particularly in transitional economies experiencing a rapidly aging population such as China. Thus, to address this research gap, this study uses data from the 2013–2018 waves of the China Health and Retirement Longitudinal Study. To investigate the causal relationship between Internet use and MH among older adults and explore the underlying channels through which this relationship operates. The results reveal a notable positive association between Internet use and MH among older adults. Furthermore, the study highlights social interaction, social trust, traveling expenses, and healthy habits as crucial channels through which Internet use can impact MH among older adults. The analysis also reveals how Internet use demonstrates a stronger positive effect on older individuals who have fewer chronic diseases and live with their offspring compared with their counterparts. These findings have significant policy implications, which thus emphasizes the need to enhance Internet use among older adults as a means of improving their MH
Glacier mass balance in the Nyainqentanglha mountains between 2000 and 2017 retrieved from ZiYuan-3 stereo images and the SRTM DEM
No full textMountain glaciers are excellent indicators of climate change and have an important role in the terrestrial water cycle and food security in many parts of the world. Glaciers are the major water source of rivers and lakes in the Nyainqentanglha Mountains (NM) region, where the glacier area has the second largest extent on the Tibetan Plateau. The potential of the high spatial resolution ZiYuan-3 (ZY-3) Three-Line-Array (TLA) stereo images to retrieve glacier mass balance has not been sufficiently explored. In this study, we optimized the procedure to extract a Digital Elevation Model (DEM) from ZY-3 TLA stereo images and estimated the geodetic mass balance of representative glaciers in the two typical areas of the NM using ZY-3 DEMs and the C-band Shuttle Radar Topography Mission (SRTM) DEM in three periods, i.e., 2000-2013, 2013-2017 and 2000-2017. The results provide detailed information towards better understanding of glacier change and specifically show that: (1) with our new stereo procedure, ZY-3 TLA data can significantly increase point cloud density and decrease invalid data on the glacier surface map to generate a high resolution (5 m) glacier mass balance map; (2) the glacier mass balance in both the Western Nyainqentanglha Mountains (WNM) and Eastern Nyainqentanglha Mountains (ENM) was negative in 2000-2017, and experienced faster mass loss in recent years (2013-2017) in the WNM. Overall, the glaciers in the western and eastern NM show different change patterns since they are influenced by different climate regimes; the glacier mass balances in WNM was-0.22 ± 0.23 m w.e. a-1 and-0.43 ± 0.06 m w.e. a-1 in 2000-2013 and 2013-2017, respectively, while in 2000-2017, it was-0.30 ± 0.19 m w.e. a-1 in the WNM and-0.56 ± 0.20 m w.e. a-1 in the ENM; (3) in the WNM, the glaciers experienced mass loss in 2000-2013 and 2013-2017 in the ablation zone, while in the accumulation zone mass increased in 2000-2013 and a large mass loss occurred in 2013-2017; as regards the ENM, the glacier mass balance was negative in 2000-2017 in both zones; (4) glacier mass balance can be affected by the fractional abundance of debris and glacier slope; (5) the glacier mass balances retrieved by ZY-3 and TanDEM-X data agreed well in the ablation zone, while a large difference occurred in the accumulation zone because of the snow/firn penetration of the X-band SAR signal.Optical and Laser Remote Sensin
Inter- and Intra-Annual Glacier Elevation Change in High Mountain Asia Region Based on ICESat-1&2 Data Using Elevation-Aspect Bin Analysis Method
No full textGlaciers are sensitive indicators of climate change and have a significant influence on regional water cycle, human survival and social development. Global warming has led to great changes in glaciers over the High Mountain Asia (HMA) region. Glacier elevation change is a measure of glacier mass balance driven by the processes of energy and mass exchange between the glacier surface and the atmosphere which are influenced by climatic factors and glacier surface properties. In this study, we estimated the inter-annual and intra-annual elevation changes of glaciers in the HMA region in 2003–2020 using Ice, Cloud and land Elevation Satellite (ICESat) data and Shuttle Radar Terrain Mission (SRTM) digital elevation model (DEM) data by developing an “elevation-aspect bin analysis method” that considered the difference of glacier elevation changes in different elevations and aspects of glacier topography. The results showed that: (1) The inter-annual change of glacier elevation in 2003–2020 had large spatial heterogeneity. Glacier elevation reduction mainly occurred in the marginal region of the HMA with the maximum decline in the Nyainqentanglha region, while glacier elevation showed increase in the West Kunlun of inner HMA regions in 2003–2020. The glacier elevation change rate showed an accelerating reduction trend in most of the HMA regions, except in the west HMA where the glacier elevation reduction rate showed slowdown tendency. Specifically, the glacier elevation change rate in the entire HMA was −0.21 ± 0.12 m/year in 2003–2008 and −0.26 ± 0.11 m/year in 2003–2020, respectively. (2) The intra-annual change of HMA glacier elevation in 2019 and 2020 showed obvious spatiotemporal heterogeneity, and the glacier thickening period was gradually delayed from the marginal area to the inner area of the HMA. The glaciers in the western marginal part of the HMA (the Tienshan Mountains, Pamir and Hindu Kush and Spiti Lahaul) and Karakoram thickened in winter or spring, the glaciers in the Nyainqentanglha Mountains exhibited spring accumulation. The glaciers in West Kunlun accumulated in two time periods, i.e., from March to June and from July to September. The glaciers in the Inner Tibetan Plateau and Bhutan and Nepal areas experienced spring or summer accumulation, especially in June or July. Moreover, we found that the inter-annual and intra-annual change of glacier elevation could be explained by the changes in temperature and precipitation. A similar analysis can be extended to mountain glaciers in other regions of the world, and glacier change trends could be further explored over a longer time span with the continuous operation of ICESat-2
Glacier Mass Balance in the Kangri Karpo Mountains by ZY-3 Stereo Images and SRTM DEMs Between 2000 and 2017
No full textBearing Fault Diagnosis Method based on RLMD and Kmeans++
No full textTo improve the performance of bearing fault diagnosis， a bearing fault diagnosis method based on Robust Local Mean Decomposition （RLMD） and Kmeans++ is proposed. The product functions （PF） are obtained by decomposing the bearing vibration signal using the RLMD technique. The sensitive PF components are sifted by calculating the correlation coefficients between the PF components and the original vibration signal， and the sensitive PF components are superimposed to form the reconstructed signal. The bearing fault feature set is formed by calculating the time and frequency domain statistical features of the original vibration signal and the reconstructed signal. The Fisher features of bearing failure feature are extracted by linear discriminant analysis （LDA）. The fault feature is clustered by the Kmeans++ clustering method and the cluster center of each bearing working condition is got. The bearing fault identification is realized by calculating the Hamming approach degree between the test sample and the cluster center. The simulated bearing data with different signal-to-noise ratios and bearing data from the Paderborn university test bench are used to evaluate the effectiveness of the proposed method. Results show that the proposed method can accurately identify bearing faults with different categories and levels even though the number of training sample is small
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